The challenging deployment of compute-intensive applications from domains such as
Artificial Intelligence (AI) and Digital Signal Processing (DSP), forces the community of …

When a computational task tolerates a relaxation of its specification or when an algorithm
tolerates the effects of noise in its execution, hardware, system software, and programming …

3D perception in point clouds is transforming the perception ability of future intelligent
machines. Point cloud algorithms, however, are plagued by irregular memory accesses …

Deep convolutional neural networks (DCNNs) are one of the most promising deep learning
techniques and have been recognized as the dominant approach for almost all recognition …

Approximate computing is the idea that systems can gain performance and energy efficiency
if they expend less effort on producing a “perfect” answer. Approximate computing …

Loop perforation is one of the most well known software techniques in approximate
computing. It transforms loops to periodically skip subsets of their iterations. It is general …

Memory subsystems are a major energy bottleneck in computing platforms due to frequent
transfers between processors and off-chip memory. We propose approximate memory …

High interconnect bandwidth is crucial to achieve better performance in many-core GPGPU
architectures that execute highly data parallel applications. The parallel warps of threads …

Growing interest towards the development of smart Cyber Physical Systems (CPS) and
Internet of Things (IoT) has motivated the researchers to explore the suitability of carrying out …

In this paper, we identify a previously untapped source of compressibility in cache working
sets: clusters of cachelines that are similar, but not identical, to one another. To compress …